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Distribution network restoration supply method considers 5G base station energy storage participation

Author

Listed:
  • Wang, Xiaowei
  • Kang, Qiankun
  • Gao, Jie
  • Zhang, Fan
  • Wang, Xue
  • Qu, Xinyu
  • Guo, Liang

Abstract

This paper proposes a distribution network fault emergency power supply recovery strategy based on 5G base station energy storage. This strategy introduces Theil's entropy and modified Gini coefficient to quantify the impact of power supply reliability in different regions on base station backup time, thereby establishing a more accurate base station's backup energy storage capacity model that can fully utilize the base station's energy storage resources to participate in the emergency power supply of distribution network faults. First, the optimal Copula function in each cycle is determined through the Akaike information criterion and squared Euclidean distance to establish a wind power-photovoltaic output scenario. Secondly, the traditional Gini coefficient is modified using the weighted average node degree and influence rate indicators. A comprehensive vulnerability model is established through the modified Gini coefficient and Theil's entropy indicators. Based on the comprehensive vulnerability model, a backup energy storage time model and a modified backup energy storage capacity model of the base station affected by power supply reliability are established. Thus, the callable energy storage capacity of base stations in different areas is obtained. Finally, a two-stage robust optimization model is introduced to minimize system operating costs to solve the volatility of 5G base station communications and wind-solar output, thereby establishing an emergency power supply recovery model for base station energy storage and wind-solar output. Simulated with the improved IEEE-33 node model, the results show that the proposed base station's energy storage model improves the utilization of the base station energy storage resources and, at the same time, effectively reduces the loss of load during the fault phase of the distribution network and improves the absorption of the PV output.

Suggested Citation

  • Wang, Xiaowei & Kang, Qiankun & Gao, Jie & Zhang, Fan & Wang, Xue & Qu, Xinyu & Guo, Liang, 2024. "Distribution network restoration supply method considers 5G base station energy storage participation," Energy, Elsevier, vol. 289(C).
    • Handle: RePEc:eee:energy:v:289:y:2024:i:c:s036054422303219x
    DOI: 10.1016/j.energy.2023.129825
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    References listed on IDEAS

    as
    1. Qiu, Haifeng & You, Fengqi, 2020. "Decentralized-distributed robust electric power scheduling for multi-microgrid systems," Applied Energy, Elsevier, vol. 269(C).
    2. Dong, Yuchen & Zheng, Weibo & Cao, Xiaoyu & Sun, Xunhang & He, Zhengwen, 2023. "Co-planning of hydrogen-based microgrids and fuel-cell bus operation centers under low-carbon and resilience considerations," Applied Energy, Elsevier, vol. 336(C).
    3. Krishna, Attoti Bharath & Abhyankar, Abhijit R., 2023. "Time-coupled day-ahead wind power scenario generation: A combined regular vine copula and variance reduction method," Energy, Elsevier, vol. 265(C).
    4. Wang, Peng & Li, Yanting & Zhang, Guangyao, 2023. "Probabilistic power curve estimation based on meteorological factors and density LSTM," Energy, Elsevier, vol. 269(C).
    5. Dahal, Madhu Sudan & Shrestha, Jagan Nath & Shakya, Shree Raj, 2018. "Energy saving technique and measurement in green wireless communication," Energy, Elsevier, vol. 159(C), pages 21-31.
    6. Hou, Hui & Tang, Junyi & Zhang, Zhiwei & Wang, Zhuo & Wei, Ruizeng & Wang, Lei & He, Huan & Wu, Xixiu, 2023. "Resilience enhancement of distribution network under typhoon disaster based on two-stage stochastic programming," Applied Energy, Elsevier, vol. 338(C).
    7. Mohseni, Soheil & Khalid, Roomana & Brent, Alan C., 2023. "Stochastic, resilience-oriented optimal sizing of off-grid microgrids considering EV-charging demand response: An efficiency comparison of state-of-the-art metaheuristics," Applied Energy, Elsevier, vol. 341(C).
    8. He, Xitian & Sun, Bingxiang & Zhang, Weige & Su, Xiaojia & Ma, Shichang & Li, Hao & Ruan, Haijun, 2023. "Inconsistency modeling of lithium-ion battery pack based on variational auto-encoder considering multi-parameter correlation," Energy, Elsevier, vol. 277(C).
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    Cited by:

    1. Zhang, Zenghui & Zhou, Kaile & Yang, Shanlin, 2024. "A post-disaster load supply restoration model for urban integrated energy systems based on multi-energy coordination," Energy, Elsevier, vol. 303(C).

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